GAFFE: A Gaze-Attentive Fixation Finding Engine

Rajashekar, Umesh and van der Linde, Ian and Bovik, Alan C. and Cormack, Lawrence K. (2008) GAFFE: A Gaze-Attentive Fixation Finding Engine. IEEE Transactions on Image Processing, 17 (4). pp. 564-573. ISSN 1941-0042

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The ability to automatically detect visually interesting regions in images has many practical applications, especially in the design of active machine vision and automatic visual surveillance systems. Analysis of the statistics of image features at observers' gaze can provide insights into the mechanisms of fixation selection in humans. Using a foveated analysis framework, we studied the statistics of four low-level local image features: luminance, contrast, and bandpass outputs of both luminance and contrast, and discovered that image patches around human fixations had, on average, higher values of each of these features than image patches selected at random. Contrast-bandpass showed the greatest difference between human and random fixations, followed by luminance-bandpass, RMS contrast, and luminance. Using these measurements, we present a new algorithm that selects image regions as likely candidates for fixation. These regions are shown to correlate well with fixations recorded from human observers.

Item Type: Journal Article
Faculty: ARCHIVED Faculty of Science & Technology (until September 2018)
Depositing User: Repository Admin
Date Deposited: 06 Feb 2014 13:57
Last Modified: 09 Sep 2021 16:18

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